Chen BWang H.-MChien L.-FLIN-SHAN LEE2023-06-092023-06-091998https://www.scopus.com/inward/record.uri?eid=2-s2.0-0001079615&partnerID=40&md5=556c0ccec3d637fd63b6f3bc10e9fb98https://scholars.lib.ntu.edu.tw/handle/123456789/632409In this paper, we propose an A*-admissible key-phrase spotting framework, which needs little domain knowledge and is capable of extracting salient key-phrase fragments from an input utterance in real-time. There are two key features in our approach. Firstly, the acoustic models and the search framework are specially designed such that very high degree vocabulary flexibility can be achieved for any desired application tasks. Secondly, the search framework uses an efficient two-pass A* search to generate N-best key-phrase candidates and then several sub-syllable level verification functions are properly weighted and used to further improve the recognition accuracy. Experimental results show that the A*-admissible key-phrase spotting with sub-word level utterance method outperforms the baseline methods used in common approaches. © 1998. 5th International Conference on Spoken Language Processing, ICSLP 1998. All rights reserved.Acoustics model; Application tasks; Domain knowledge; Key feature; Key-phrase; Real- time; Recognition accuracy; Sub words; Utterance verification; Word level; Domain Knowledgeconference paper2-s2.0-0001079615